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The Correlation Between Hyperglycemia and Rheumatoid Factor in Type 2 Diabetic Patients in Al- Risafa Area, Baghdad
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Diabetes mellitus type 2 (T2DM) formerly called non-insulin dependent diabetes mellitus (NIDDM) or adult-onset diabetes is a common disease. Rheumatoid factor is a well-established test used in the diagnosis and follows the prognosis of rheumatoid arthritis (RA). Rheumatoid factor is sometimes found in serum of patients with other diseases including diabetes mellitus (DM), due to the presence of pro-inflammatory cytokines such as TNF- α which play an important role in chronic inflammatory and autoimmune diseases like rheumatoid arthritis (RA). The aim of the study is to investigate the associations between type 2 diabetes mellitus (T2DM) and rheumatoid arthritis (RA) in scope of rheumatoid factor (RF), hyperglycemia and body mass index (BMI), in patients with T2DM lived in Al-Risafa area -Baghdad. One hundred twenty five (125) type 2 diabetes mellitus (T2DM) patients were selected from the out patients department of the Specialized Center for Endocrinology and Diabetes, Baghdad; in addition to (70) apparently healthy non diabetic, non arthritic subjects as control, during the period from Sep. - Dec./2010. The ages of both patients and control subjects were within (35-75) years. This study focus to search for the correlation between T2DM and RF "qualitative and quantitative" in relation to body mass index (BMI) and gender. Out of 125 DM-patients (73 female and 52 male), 44 (35.2 %) showed positive RF when compared with healthy controls (N=3, 4.3%). [P value =0.01 is significant] with female dominance (N=28, 63.6%) in compared to males (N=16, 36.4 %), when these diabetics with RF positive were titered for RF (8, 16, 32 and 64 IU/ml), the following results were obtained. The highest percentage of titer observed with 34.1% in those with RF titer 64 IU/ ml [P value = 0.01] when compared with healthy control.  18.2 % had RF titer of 8 IU/ ml, 20.4 % had RF titer of 16 IU/ ml, 27.3 % had RF titer of 32 IU/ ml and 34.1 % had RF titer of 64 IU/ ml. The highest percentage among the overweight, DM patients (38.9 %) have a mean titer 64 IU/ml, a percentage decrease respectively as below: 38.9 % had RF titer of 64 IU/ ml, 27.8% had RF titer of 32 IU/ ml, 16.6 % had RF titer 16 IU / ml and 16.6% had RF titer 8 IU/ ml. The highest number and percentage of DM with RF positive (N=17, 38.6 %) were located among higher age (50-59), (60-69) & (70 -79) year groups (N=17, 38.6%), (N=13, 29.5%) & (N=8, 18.2%) respectively, [P- Value < 0.01] when compared to the corresponding controls. The effect of fasting plasma glucose level of type 2 DM in patients who have RF positive titer, is found that > 7.2 mmol/l glucose in plasma contribute the highest titer (N=28, 63.6 %), in comparison with group of plasma glucose levels < 7.2 mmol/l patients (N=16, 36.4%). with a highly significant difference, P-value = 0.006.Smokers diabetic patients with RF positive (N=27, 61.4%) dominate over non- smokers with RF positive (N=17, 38.6%). The results of this study indicate that there is a reasonable increased frequency of positive rheumatoid factor (RF) in type 2 diabetic patients. Poor glycemic control is associated with higher RF titer in positive cases. The titer of T2DM smoker patients is associated with positive RF values that exceed the titer of the non- smoker RF positive patients. Thus, smoking might not be correlated significantly to DM, but may contribute to its complications.

Key words: T2DM, RF, BMI, Smoking.

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Publication Date
Sun Jun 01 2025
Journal Name
Chemical Engineering And Processing - Process Intensification
Wastewater treatment through a hybrid electrocoagulation and electro-Fenton process with a porous graphite air-diffusion cathode
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Publication Date
Wed Mar 01 2023
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
Design and implementation monitoring robotic system based on you only look once model using deep learning technique
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<span lang="EN-US">The need for robotics systems has become an urgent necessity in various fields, especially in video surveillance and live broadcasting systems. The main goal of this work is to design and implement a rover robotic monitoring system based on raspberry pi 4 model B to control this overall system and display a live video by using a webcam (USB camera) as well as using you only look once algorithm-version five (YOLOv5) to detect, recognize and display objects in real-time. This deep learning algorithm is highly accurate and fast and is implemented by Python, OpenCV, PyTorch codes and the Context Object Detection Task (COCO) 2020 dataset. This robot can move in all directions and in different places especially in

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Wed Aug 01 2012
Journal Name
International Journal Of Geographical Information Science
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Publication Date
Sat Oct 01 2022
Journal Name
Advances In Structural Engineering
Experimental and FE analysis of composite RC beams with encased pultruded GFRP I-beam under static loads
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Encasing glass fiber reinforced polymer (GFRP) beam with reinforced concrete (RC) improves stability, prevents buckling of the web, and enhances the fire resistance efficiency. This paper provides experimental and numerical investigations on the flexural performance of RC specimens composite with encased pultruded GFRP I-sections. The effect of using shear studs to improve the composite interaction between the GFRP beam and concrete was explored. Three specimens were tested under three-point loading. The deformations, strains in the GFRP beams, and slippages between the GFRP beams and concrete were recorded. The embedded GFRP beam enhanced the peak loads by 65% and 51% for the composite specimens with and without shear connectors,

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Simplified Novel Approach for Accurate Employee Churn Categorization using MCDM, De-Pareto Principle Approach, and Machine Learning
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Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

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Publication Date
Mon Apr 03 2023
Journal Name
Polymer Composites
Effect of silver nanoparticles on structural, thermal, electrical, and mechanical properties of poly(vinyl alcohol) polymer nanocomposites
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Publication Date
Wed May 01 2019
Journal Name
Environmental Technology &amp; Innovation
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Publication Date
Thu Oct 29 2020
Journal Name
Complexity
Training and Testing Data Division Influence on Hybrid Machine Learning Model Process: Application of River Flow Forecasting
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The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

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Publication Date
Tue Feb 01 2022
Journal Name
Journal Of Ovonic Research
Effect of copper on physical properties of CdO thin films and n-CdO: Cu / p-Si heterojunction
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Publication Date
Mon Nov 11 2019
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Day 3 Wed, November 13, 2019
Drill Bit Selection Optimization Based on Rate of Penetration: Application of Artificial Neural Networks and Genetic Algorithms
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Abstract<p>The drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the</p> ... Show More
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