Fatty acids, particularly omega-3, omega-6, and omega-9, play a vital role in various biological processes. As the body cannot synthesize omega-3 and omega-6, dietary sources of these fatty acids are essential. Each omega fatty acid has a distinct chemical structure, source, and function. Cisplatin (CP) treatment is known to cause acute kidney injury (AKI) due to its inflammatory effects. This study explored the renoprotective potential of omega-3-6-9 when co-ad-ministered with cisplatin in a mice model. We divided adult mice into five groups: a control group received 0.5 ml of liquid paraffin; a cisplatin-only group; two groups were treated with low (50 mg/kg) and high (100 mg/kg) doses of omega-3-6-9 plus cisplatin; and a final group rece

Central banks around the world typically use various financial indicators to evaluate performance. In Iraq, the indicators used by central banks to evaluate the performance of banks are of great importance to ensure that the banks operating within the Iraqi banking system comply with the regulatory and legal requirements issued by the Central Bank of Iraq or the Ministry of Finance. Given the need to study the profitability indicator to ensure its ability to evaluate the performance of specialized banks in Iraq, these banks carry out their banking activities and businesses through capital funded by the government. The use of profitability indicators in evaluating the performance of specialized banks provides information about the profitabil

ABSTRACT                                                                                            

The study aims to identify the level of health services provided in private suites to government hospitals from the perspective of the recipi

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

Acinetobacter baumannii received attention for its multi-drug resistant associated with many severe infections and outbreaks in clinical environment. The aims of the study are to investigate the antibiotic susceptibility profile of clinically isolated A. baumannii, biofilm production, and the efficiency of Low Frequency Ultrasound (LFU) and honey to attenuate biofilm production. A total of 100 samples were taken from different sources from Baghdad hospitals. The susceptibility patterns revealed the percentage of pan drug resistant (PDR) isolates were 1.5 %, 72.7 % were extended drug resistant (XDR), 16.7 % were multidrug resistant (MDR), and 9.1 % were non MDR and sensitive to most antibiotics used. The ability to form

The nephrotoxicity induced by methotrexate is a severe condition that greatly affects its therapeutic potential and has a significant inflammatory component. Fimasartan is an angiotensin receptor blocker that offers organ-protective effects and may be useful in mitigating renal injury. The present study explored the anti-inflammatory potential of two doses of fimasartan against methotrexate-mediated nephrotoxicity. Albino rats were intraperitoneally administered a single methotrexate (20 mg/kg). Intraperitoneal treatment with fimasartan (5 or 10 mg/kg/day) was initiated on day two after methotrexate injection and continued for seven consecutive days. Methotrexate significantly increased serum urea, creatinine, and NGAL concentrations. It al

The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed

Abstract

This research aim to overcome the problem of dimensionality by using the methods of non-linear regression, which reduces the root of the average square error (RMSE), and is called the method of projection pursuit regression (PPR), which is one of the methods for reducing dimensions that work to overcome the problem of dimensionality (curse of dimensionality), The (PPR) method is a statistical technique that deals with finding the most important projections in multi-dimensional data , and With each finding projection , the data is reduced by linear compounds overall the projection. The process repeated to produce good projections until the best projections are obtained. The main idea of the PPR is to model

In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database