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joe-1907
Public Procurement Crisis of Iraq and its Impact on Construction Projects
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The public procurement crisis in Iraq plays a fundamental role in the delay in the implementation of construction projects at different stages of project bidding (pre, during, and after). The procurement system of any country plays an important role in economic growth and revival. The paper aims to use the fuzzy logic inference model to predict the impact of the public procurement crisis (relative importance index and Likert scale) was carried out at the beginning to determine the most important parameters that affect construction projects, the fuzzy analytical hierarchy process (FAHP) to set up, and finally, the fuzzy decision maker's (FDM) verification of the parameter for comparison with reality. Sixty-five construction projects in Iraq have been selected, and the most crucial crisis variables were used for calculating the weights and their importance, using the fuzzy logic inference model to verify the crisis parameters and the extent of their impact in preparation for predicting the mathematical model of public procurement parameters. After the algorithm had been completed, it was noted that the fast, messy genetic algorithm produced a little difference between training and testing (0.012% and 0.0057%), which is more reliable for predicting mean results from models. The paper’s major conclusion is that 18 crisis factors in public procurement through different stages affect construction projects in Iraq.

 

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Publication Date
Wed Jan 22 2020
Journal Name
Molecules
In Vivo and In Vitro Evaluation of the Protective Effects of Hesperidin in Lipopolysaccharide-Induced Inflammation and Cytotoxicity of Cell
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(1) Background: Plant flavonoids are efficient in preventing and treating various diseases. This study aimed to evaluate the ability of hesperidin, a flavonoid found in citrus fruits, in inhibiting lipopolysaccharide (LPS) induced inflammation, which induced lethal toxicity in vivo, and to evaluate its importance as an antitumor agent in breast cancer. The in vivo experiments revealed the protective effects of hesperidin against the negative LPS effects on the liver and spleen of male mice. (2) Methods: In the liver, the antioxidant activity was measured by estimating the concentration of glutathione (GSH) and catalase (CAT), whereas in spleen, the concentration of cytokines including IL-33 and TNF-α was measured. The in vitro expe

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Publication Date
Sat Dec 04 2021
Journal Name
International Journal Of Drug Delivery Technology
Evaluation of the Anti-inflammatory and Anti-oxidant Activity of Crab Components and Crab Shell in Experimental Rats in Comparison with Dexamethasone and Diclofenac Sodium
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Crabs belong to the crustacean family (Decapods crustacean), and their shells contain natural ingredients from which the bioactive compounds are derived. It has been used as folklore medicine in cancer treatment. We investigate the possible anti-inflammatory and anti-oxidant effects for crab shells and whole crabs. Thirty-six rats (150–200 gm) from both sexes were used, divided into six groups, the anti-inflammatory and anti-oxidant activity measured using cotton pellet induce granuloma model. Detection of tumor necrosis factor alpha (TNF α), Interleukin 1 beta (IL-1β), superoxide (SOD), and malondialdehyde (MDA) levels using ELISA Kits. The data analysis by one-way ANOVA followed by the Tukey test. Values are significant at (p < 0.05).

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Publication Date
Wed Mar 31 2021
Journal Name
Indones. J. Chem.,
Synthesis and DFT Study of the Complexation of Schiff Base Derived Curcumin and L-Tyrosine with Al(III), Ag(I), and Pb(II) Metal Ions
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The multi-dentate Schiff base ligand (H2L), where H2L=2,2'-(((1,3,5,6)-1-(3-((l1-oxidaneyl)-l5-methyl)-4-hydroxyphenyl)-7-(4-hydroxy-3-methoxyphenyl)hepta-1,6-di ene-3,5-diylidene)bis(azaneylylidene))bis(3-(4-hydroxyphenyl)propanoic acid), has been prepared from curcumin and L- Tyrosine amino acid. The synthesized Schiff base ligand (H2L) and the second ligand 1,10-phenanthroline (phen) are used to prepare the new complexes [Al(L)(phen)]Cl, K[Ag(L)(phen)] and [Pb(L)(phen)]. The synthesized compounds are characterized by magnetic susceptibility measurements, micro elemental analysis (C.H.N), mass spectrometry, molar conductance, FT-infrared, UV-visible, atomic absorption (AA), 13C-NMR, and 1H-NMR spectral studies. The characterization of the

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Hepatocellular Carcinoma Prediction and early Diagnosis of Hepatitis B and C viral infection using miR-122 and miR-223 in a sample of Iraqi patients.
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Hepatocellular carcinoma (HCC) is the third most common cause of cancer-related death. Therefore, it is critical for researchers to understand molecular biology in greater depth.  In several diseases including cancer, abnormal miRNA expression has been linked to apoptosis, proliferation, differentiation, and metastasis. Many miRNAs have been studied in relation to cancer, including miR-122, miR-223, and others. Hepatitis B and C viruses are the most important global risk factors for HCC. This study is intended to test whether serum miRNAs serve as a potential biomarker for both HCC and viral infections HBV and C. The expression of miRNA in 64 serum samples was analyzed by RT-qPCR. Compared to healthy volunteers, HCC patients' sera expre

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Publication Date
Tue Sep 01 2020
Journal Name
Journal Of Engineering
An Adaptive Digital Neural Network-Like-PID Control Law Design for Fuel Cell System Based on FPGA Technique
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This paper proposes an on-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. This research aims to design and implement Neural Network like a digital PID using FPGA in order to generate the best value of the hydrogen partial pressure action (PH2) to control the stack terminal output voltage of the (PEMFC) model during a variable load current applied. The on-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID-NN controller (kp, ki, and kd) parameters that improve the dynamic behavior of the closed-loop digital control fue

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Publication Date
Sun Jan 14 2018
Journal Name
Journal Of Engineering
A Nonlinear MIMO-PID Neural Controller Design for Vehicle Lateral Dynamics model based on Modified Elman Neural Network
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This paper presents a new design of a nonlinear multi-input multi-output PID neural controller of the active brake steering force and the active front steering angle for a 2-DOF vehicle model based on modified Elman recurrent neural. The goal of this work is to achieve the stability and to improve the vehicle dynamic’s performance through achieving the desired yaw rate and reducing the lateral velocity of the vehicle in a minimum time period for preventing the vehicle from slipping out the road curvature by using two active control actions: the front steering angle and the brake steering force. Bacterial forging optimization algorithm is used to adjust the parameters weights of the proposed controller. Simulation resul

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Publication Date
Thu Oct 01 2020
Journal Name
Bulletin Of Electrical Engineering And Informatics
Lightweight hamming product code based multiple bit error correction coding scheme using shared resources for on chip interconnects
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In this paper, we present multiple bit error correction coding scheme based on extended Hamming product code combined with type II HARQ using shared resources for on chip interconnect. The shared resources reduce the hardware complexity of the encoder and decoder compared to the existing three stages iterative decoding method for on chip interconnects. The proposed method of decoding achieves 20% and 28% reduction in area and power consumption respectively, with only small increase in decoder delay compared to the existing three stage iterative decoding scheme for multiple bit error correction. The proposed code also achieves excellent improvement in residual flit error rate and up to 58% of total power consumption compared to the other err

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Publication Date
Tue Jan 01 2019
Wide-range tunable subwavelength band-stop filter for the far-infrared wavelengths based on single-layer graphene sheet
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Publication Date
Tue Apr 02 2019
Journal Name
Artificial Intelligence Research
A three-stage learning algorithm for deep multilayer perceptron with effective weight initialisation based on sparse auto-encoder
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A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Simulation Study on Optically Designed Refractive Beam Expander for Nd: YAG Laser Harmonics for 7 Km Detection Range
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The simulation study has been conducted for the harmonics of Nd: YAG laser, namely the second harmonic generation SHG, the third harmonic generation THG, and the fourth harmonic generation FHG. Determination of beam expander's expansion ratio for specific wavelength and given detection range is the key in beam expander design for determining minimum laser spot size at the target. Knowing optimum expansion ratio decreases receiving unit dimensions and increases its performance efficiency. Simulation of the above mentioned parameters is conducted for the two types of refractive beam expander, Keplerian and Galilean. Ideal refractive indices for the lenses are chosen adequately for Nd: YAG laser harmonics wavelengths, so that increasing transm

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