In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and introduced. Optimal results showed that the optimum viscosity and thermal conductivity occurs at maximum temperature.
The heavy metals Cd, Cu, Fe, pb, and Zn were determined in dissolved and particulate phases of the water,in addition to exchangeable and residual phases of the sediment and in the selected organs of the fish Cyprinus carpio collected from the Euphrates River near Al-Nassiriya city center south of Iraq during the summer period / 2009 .Also sediment texture and total organic carbon(TOC) were measured. Analysis emploing a flam Atomic Absorption Spectrophotometers . The mean regional concentrations of the heavy metals in dissolved (µg/l) and particulate phases (µg/gm) dry weight were Cd (0.15,16.13) ,Cu (0.59,24.48) ,Fe (726,909.4) ,Pb (0.20, 49.95) and Zn (2.5,35.62) respectively,and those for exchangeable and residual phases of the
... Show MoreAbstract Background: The human epidermal growth factor receptor 2(HER2) proto-oncogene is overexpressed or amplified in approximately 15%-25% of invasive breast cancers. Approximately 35% of HER2-amplified breast cancers have coamplification of the topoisomerase II-alpha (TOP2A) gene encoding an enzyme that is a major target of anthracyclines. Hence, the determination of genetic alteration (amplification or deletion) of both genes is considered as an important predictive factor that determines the response of breast cancer patients to treatment. The aims of this study are to determinate TOP2A status gene amplification in a set of Iraqi patients with breast cancer that have had an equivocal (2+) and positive HER2/neu by immunohistochemistry
... Show MoreThe growth of developments in machine learning, the image processing methods along with availability of the medical imaging data are taking a big increase in the utilization of machine learning strategies in the medical area. The utilization of neural networks, mainly, in recent days, the convolutional neural networks (CNN), have powerful descriptors for computer added diagnosis systems. Even so, there are several issues when work with medical images in which many of medical images possess a low-quality noise-to-signal (NSR) ratio compared to scenes obtained with a digital camera, that generally qualified a confusingly low spatial resolution and tends to make the contrast between different tissues of body are very low and it difficult to co
... Show More. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a
... Show MoreThis study was conducted to prepare protein concentrates from AL-Zahdidate’s pits by using alkaline methods where the chemical composition of the pits were (7.30, 1.04, 5.80, 8.68 and 77.19) % for each of the moisture, ash, protein, fat and carbohydrates respectively and the chemical composition of the concentrate protein was (6.62, 4.10, 26.70, 0.93, and 58.65) % respectively. The content of protein concentrate from the metallic elements (144.07, 25.11, 15.02, 0.49, 0.59, 0.27, 0.22 and 234.6) mg/ 100 g each of potassium, magnesium, calcium, iron, manganese, copper, zinc and phosphorus respectively. The results of SDS-PAGE showed five bands with weights molecular ranged between 11000-70000 Dalton. Give the biscuit which contain protei
... Show MoreThe paper deals with the study of the sciences of the Qur’an according to the interpreter, Ayatollah Sayyid Mahmoud al-Talaqani, a religious jihadist figure from Iran. He is the author of the exegesis (Ishraq from Al-Quran), which consists of six parts, which he wrote inside the prisons of the Shah and in exile. Mr. Al-Talaqani agreed with some of the commentators in his positions on the sciences of the Qur’an, and some of them disagreed with others.
The study aimed to evaluate injuries and economic losses which caused by rose beetle Maladerainsanabilis (Brenske) on ornamental and fruit plants as introduced insect in Iraq during 2015 and determine infested host plants in addition to evaluate efficacy of pathogenic fungi Metarhiziumanisopiliae (1x10⁹ spore/ ml) and Beauvariabassiana (1x10⁸spore/ ml) in mortality of insect larvae in laboratory and field.The results showed that the insect was polyphagous infested many host plants (20 host plant)Which caused degradation and dead the plants through adult feeding on leaves and flower but large injury caused by larvae feeding on root plants which caused obligate dead to infested plant, the percentage mortality of rose plants 68.6%, pear
... Show MoreThe Tigris River, a vital water resource for Iraq, faces significant challenges due to urbanization, agricultural runoff, industrial discharges, and climate change, leading to deteriorating water quality. Traditional methods for assessing irrigation water quality, such as laboratory testing and statistical modeling, are often insufficient for capturing dynamic and nonlinear relationships between parameters. This study proposes a novel application of the Gravitational Search Algorithm (GSA) to estimate the Irrigation Water Quality Index (IWQI) along the Tigris River. Using data from multiple stations, the study evaluates spatial variability in water quality, focusing on key paramete