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The role of Cost awareness of activation of strategic cost management techniques of industrial units: A prospective study at the General Company for the manufacture of medicines and medical supplies in the province of Mosul
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The last ten years observed a shift enormous scientific in the method and way that it deals professional with the cost accounting and reflected the result those shift enormous scientific of increase the competitive environmental that accompanied the emergence of a modern manufacturing environmental on surface the long roductive life and emergence advanced information technology that give a central focus of his important on client with growing global markets growth on a large scale.

        The research aim to define the concept of cost awareness, the concept and methods of  strategic cost management and the role of cost awareness for managers of industrial units in strategic of cost management, the research premise that growing of cost awareness upon managers of industrial units will lead to provide the necessary environmental for development of efficient management of costs and then increase the effectiveness of the costs information systems.   This research find out the set of conclusions one of most important is that publishing the cost awareness and growing it at management of companies help greatly on applying the methods of strategic cost management. The researchers  recommended the needed of growing and publishing cost awareness concept at companies management and trend towards apply the methods of strategic  cost management.               

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Publication Date
Sun May 01 2022
Journal Name
Journal Of Engineering
Estimating Pitting Corrosion Depth and Density on Carbon Steel (C-4130) using Artificial Neural Networks
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The purpose of this research is to investigate the impact of corrosive environment (corrosive ferric chloride of 1, 2, 5, 6% wt. at room temperature), immersion period of (48, 72, 96, 120, 144 hours), and surface roughness on pitting corrosion characteristics and use the data to build an artificial neural network and test its ability to predict the depth and intensity of pitting corrosion in a variety of conditions. Pit density and depth were calculated using a pitting corrosion test on carbon steel (C-4130). Pitting corrosion experimental tests were used to develop artificial neural network (ANN) models for predicting pitting corrosion characteristics. It was found that artificial neural network models were shown to be

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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
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
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
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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Publication Date
Wed Aug 02 2023
Journal Name
Contemporary Trends And Issues In Science Education
Using Multi-faceted Rasch Models to Understand Middle School Students’ Argumentation Around Scenarios Grounded in Socio-scientific Issues
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Publication Date
Sun Aug 05 2018
Journal Name
Journal Of Entomology And Zoology Studies
Some biochemical traits in broiler chicken as affected by insulin-like growth factor-1 (IGF-1) gene polymorphisms
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This study was conducted during the period 1/9/2014 – 1/2/2015 and aimed to identify the polymorphisms of IGF-1 gene in broiler chickens and their effects on some biochemical traits. A total of 300 one-day-old broiler chicks (Cobb500, n=150; Hubbard F-15, n=150) were evaluated in this study. Blood samples were individually collected from all birds for DNA extraction. PCR-RFLP method being used for determination the genotypes of IGF-1 gene which then correlated with biochemical traits studied. Cobb500 broilers with TT genotype had significantly (p˂0.05) higher serum triglycerides values than those of TC and CC genotypes. Low density lipoprotein (LDL) were significantly (p˂0.05) higher in Hubbard F-15 broilers with TT genotype than those

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Publication Date
Tue Jan 25 2011
Journal Name
Journal Of Cellular Biochemistry
Phytoestrogens directly inhibit TNF-α-induced bone resorption in RAW264.7 cells by suppressing c-fos-induced NFATc1 expression
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TNF-α-induced osteoclastogenesis is central to post-menopausal and inflammatory bone loss, however, the effect of phytoestrogens on TNF-α-induced bone resorption has not been studied. The phytoestrogens genistein, daidzein, and coumestrol directly suppressed TNF-α-induced osteoclastogenesis and bone resorption. TRAP positive osteoclast formation and resorption area were significantly reduced by genistein (10(-7) M), daidzein (10(-5) M), and coumestrol (10(-7) M), which was prevented by the estrogen antagonist ICI 182,780. TRAP expression in mature TNF-α-induced osteoclasts was also significantly reduced by these phytoestrogen concentrations. In addition, in the presence of ICI 182,780 genistein and coumestrol (10(-5) -10(-6) M) augmente

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Publication Date
Wed Nov 13 2019
Journal Name
J. Pharm. Sci. & Res.
Mandibular Degree II Furcation Defect Treatment With 1%Alendronate Gel Alone or In Combination with Platelet- Rich Fibrin
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