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Study of the reliability of serum vascular endothelial growth factor and its soluble receptor as markers of diabetic nephropathy in type 2 diabetes patients
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The levels of circulating angiogenic and anti-angiogenic factors, namely vascular endothelial growth factor–A (VEGF-A) and soluble vascular endothelial growth factor receptor-1 (sVEGFR-1), have been linked to the development of renal dysfunction due to the proliferation of microvasculature within the kidneys of type 2 diabetic (T2DM) patients. The study aims to scrutinize serum levels of VEGF and sVEGFR-1 in a sample of Iraqi diabetic nephropathy patients to support their reliability as markers for the prediction of nephropathy in type 2 diabetes mellitus patients as well as to assess the ACE inhibitor’s effect on the levels of these two markers. Method: The ninety participants of this case-control study were split into three groups: thirty-five patients with T2DM and an equal number of patients with DN and the third group involve twenty apparently healthy individuals as the control group. The two diabetic groups have been further divided into four groups according to the ACE inhibitors use. Laboratory measurements involve the glycemic indices, renal function test with serum VEGF-A and sVEGFR-1. Results: the median serum levels of VEGF-A show valuable discrepancies between the three groups (p-value<0.05) but for sVEGFR-1 it doesn’t show a notable difference between the DM and the DN groups only(p-value> 0.05).

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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Composites For Construction
Near-Surface-Mounted CFRP for Strengthening Concavely Curved Soffit RC Beams: Experimental and Analytical Investigation
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Publication Date
Thu Jun 30 2022
Journal Name
International Journal Of Drug Delivery Technology
New Metal Complexes Derived from Heterocyclic Schiff-base Ligand; Preparation, Structural Investigation and Biological Activity
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The formation of a Schiff-base with N2O2 donor atoms derived from the hydrazine segment and its metal complexes are reported. The Schiff-base ligand; N’-((1R,2S,4R,5S,Z)-2,4-diphenyl-3-azabicyclo[3.3.1]nonan-9-ylidene)furan-2-carbohydrazide (HL) was prepared from the reaction of furan-2-carbohydrazide with (1R, 2R, 4R, 5S)-2,4-diphenyl-3-azabicyclo[3.3.1]nonan-9-one (M1) in ethanol medium. The reaction of the title ligand with selected metal ions Cr(III), Mn(II), Ni(II), Cu(II), Zn(II) and Cd(II) gave complexes with the general formula [M(L)Cl2], (where: M = Cr(III), Mn(II), Ni(II), Cu(II), Zn(II) and Cd(II)). Spectroscopic analyses Fourier transform infrared (FT-IR), Nuclear Magnetic Resonance (NMR) Carbon-13 nuclear magnetic res

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Publication Date
Tue Nov 19 2024
Journal Name
Discover Sustainability
Groundwater quality assessment and pollution sources identification using statistical analyses at Missan Governorate, Southeast Iraq
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The shortage in surface water quantities led to a shift in dependence on the groundwater as an alternative water source in southern parts of Iraq. The groundwater is decreasing in quantity and water quality is degrading due to different factors. Therefore, it is important to assess the groundwater quality of the Missan Governorate of the country by analyzing the physicochemical parameters and distinguishing the probable sources of contaminants in the area. The present study used water quality diagrams and statistical methods such as factor analysis and agglomerative cluster analysis to determine the sources of chemical ions in the forty-four groundwater samples collected from wells in the study area. In addition, the Water Quality Index (WQ

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Publication Date
Sat Jun 01 2019
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Lung cancer classification using data mining and supervised learning algorithms on multi-dimensional data set
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These With recent developments in machine learning, data mining and computer vision, there is great potential for improvements in early detection of lung cancer using scans and data available. This paper details the methods and techniques used in our project, where the objective is to develop algorithms to determine whether a patient has or is likely to develop lung cancer using dataset images using data mining and machine learning for the classification and examination. We explore approaches to address the problem. Cancer is the most important cause of death globally. The disease diagnosis is a major process to treat the patients who are affected by cancer disease. The diagnosis process is more difficult comparatively known about t

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Publication Date
Wed Sep 17 2025
Journal Name
Molecular Biology Reports
Antibacterial effect and MexA efflux pump Inhibition by green-synthesized copper nanoparticles from Mentha piperita
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Publication Date
Tue May 23 2023
Journal Name
Journal Of Sensors
On-Board Digital Twin Based on Impedance and Model Predictive Control for Aerial Robot Grasping
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Aerial manipulation of objects has a number of advantages as it is not limited by the morphology of the terrain. One of the main problems of the aerial payload process is the lack of real-time prediction of the interaction between the gripper of the aerial robot and the payload. This paper introduces a digital twin (DT) approach based on impedance control of the aerial payload transmission process. The impedance control technique is implemented to develop the target impedance based on emerging the mass of the payload and the model of the gripper fingers. Tracking the position of the interactional point between the fingers of gripper and payload, inside the impedance control, is achieved using model predictive control (MPD) approach.

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Early Diagnose Alzheimer's Disease by Convolution Neural Network-based Histogram Features Extracting and Canny Edge
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Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of

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Publication Date
Wed May 10 2023
Journal Name
Biomass Conversion And Biorefinery
Lactic acid-based deep eutectic solvents and activated carbon for soap removal from crude biodiesel
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Publication Date
Thu Feb 05 2026
Journal Name
Polymers
A Flexible, Antibacterial Platform: Silver-Tuned Polyvinyl Alcohol with Enhanced Opto-Mechanical and Electrical Properties
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Silver/polyvinyl alcohol (Ag/PVA) nanocomposite films were synthesized via solution casting with varying concentrations of Ag nanoparticles (1–5 wt%). A comprehensive investigation was conducted to understand the influence of Ag content on the structural, optical, mechanical, thermal, electrical, and antibacterial properties of the composites. UV-Vis spectroscopy revealed a red shift in absorption peaks and a reduction in the optical band gap, which decreased from 3.78 eV for pure PVA to 3.37 eV for the 5 wt% Ag composite. FTIR and SEM analyses confirmed successful nanoparticle incorporation and morphological changes. The nanocomposites exhibited enhanced tensile strength, elongation at break, Young’s modulus, and hardness due t

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Publication Date
Mon Jun 01 2026
Journal Name
Chemical Physics Impact
High-density perovskite oxide ceramics with enhanced proton stopping power and gamma-ray shielding efficiency
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