The objective of the research is to measure the impact of social responsibility on the financial performance of the National Bank of Iraq for the period from 2014 to 2016 (3 years) through discussing and analyzing the level of practice of the Bank of Baghdad for social responsibility and the impact on their financial performance during the period. To measure the independent variable (CSR), the researcher used the CSR Disclosure Index and relied on the ROA as an indicator to measure the dependent variable (financial performance). The results of the research showed the main hypothesis of the research, which states that the social responsibility of the banks has no significant impact on the financial performance. In relation to the disclosure of social responsibility and ROA used. The research concluded with a number of conclusions, the study concluded a number of conclusions. The most important of these was that the adoption of social responsibility activities by the Iraqi National Bank in general was limited on the basis of the results achieved, reflecting the lack of a culture of social commitment and the consequences of its work on society and the country in which it operates. Its financial performance in general due to the results reached as it did not rise to the global benchmark associated with banking (standard ratios) according to the index used by the researcher to measure the financial performance of banks.
استخلص عامل التلزن من E. faecalis EM1 بعد تكسير الخلايا بعدة طرق واختيار الطريقة التي تعطي اعلى قيمة تلزن والترسيب بالكحول الاثيلي , واجري فحص التلزن وقياسه للمستخلص مع انواع من البكتريا السالبة لملون غرام تضمنت Escherichia coli و Klebsiella pneumoniae و Serratia
The scholars of Iraq in the modern and contemporary era have been interested in the definition of tremendous knowledge treasures left by the successive Iraqi civilizations on Mesopotamia and around the cities, through the census and extrapolation of manuscript heritage and even printed, they compiled indexes,evidence
The aim of this study was to increasing natural carotenoides production by a locally isolate Rodotorula mucilagenosa M. by determination of the optimal conditions for growth and production of this agents, for encouragest to use it in food application permute artificial pigments which harmfull for consumer health and envieronmental. The optimal condition of carotenoides production from Rhodotorula mucilaginosa M were studied. The results shows the best carbon and nitrogen source were glucose and yeast extract. The carotenoids a mount production was 47430 microgram ̸ litter and 47460 microgram ̸ litter, respectively, and the optimum temperature was 30°C, PH 6, that the carotenoides a mount was 47470 microgram ̸ litter and 47670 microgr
... Show MoreThe paper discusses the structural and optical properties of In2O3 and In2O3-SnO2 gas sensor thin films were deposited on glass and silicon substrates and grown by irradiation of assistant microwave on seeded layer nucleated using spin coating technique. The X-ray diffraction revealed a polycrystalline nature of the cubic structure. Atomic Force Microscopy (AFM) used for morphology analysis that shown the grain size of the prepared thin film is less than 100 nm, surface roughness and root mean square for In2O3 where increased after loading SnO2, this addition is a challenge in gas sensing application. Sensitivity of In2O3 thin film against NO2 toxic gas is 35% at 300oC. Sensing properties were improved after adding Tin Oxide (SnO2) to be mo
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
... Show MoreIn this work, new Schiff bases of quinazolinone derivatives (Q1-Q5) were synthesized from methyl anthranilate. The synthesis involved three steps. In the first step, methyl anthranilate was reacted with isothiocyanatobenzene, producing the thiourea derivative K1. The second step entailed reacting K1 with hydrazine hydrate, synthesizing 3-amino-2-(phenylamino) quinazolin-4(3H)-one (K2). The third step involved reaction of K2 with various aromatic aldehydes, yielding the Schiff bases derivatives Q1-Q5. The chemical structures of these compounds were identified by FT-IR,1H NMR and 13C NMR spectroscopy. The newly synthesized derivatives (Q1-Q5) were subjected to rigorous evaluation to assess their efficacy as corrosion inhibitors for ca
... Show MoreTwo dimensional meso-scale concrete modeling was used in finite element analysis of plain concrete beam subjected to bending. The plane stress 4-noded quadrilateral elements were utilized to model coarse aggregate, cement mortar. The effect of aggregate fraction distribution, and pores percent of the total area – resulting from air voids entrapped in concrete during placement on the behavior of plain concrete beam in flexural was detected. Aggregate size fractions were randomly distributed across the profile area of the beam. Extended Finite Element Method (XFEM) was employed to treat the discontinuities problems result from double phases of concrete and cracking that faced during the finite element analysis of concrete beam. Crac
... Show MoreGround-based active optical sensors (GBAOS) have been successfully used in agriculture to predict crop yield potential (YP) early in the season and to improvise N rates for optimal crop yield. However, the models were found weak or inconsistent due to environmental variation especially rainfall. The objectives of the study were to evaluate if GBAOS could predict YP across multiple locations, soil types, cultivation systems, and rainfall differences. This study was carried from 2011 to 2013 on corn (Zea mays L.) in North Dakota, and in 2017 in potatoes in Maine. Six N rates were used on 50 sites in North Dakota and 12 N rates on two sites, one dryland and one irrigated, in Maine. Two active GBAOS used for this study were GreenSeeker and Holl
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