Recently the use of nanofluids represents very important materials. They are used in different branches like medicine, engineering, power, heat transfer, etc. The stability of nanofluids is an important factor to improve the performance of nanofluids with good results. In this research two types of nanoparticles, TiO₂ (titanium oxide) and γ-Al₂O₃ (gamma aluminum oxide) were used with base fluid water. Two-step method were used to prepare the nanofluids. One concentration 0.003 vol. %, the nanoparticles were examined. Scanning Electron Microscopy (SEM), Atomic Force Microscopy (AFM) and X-ray diffraction (XRD) were used to accomplish these tests. The stability of the two types of nanofluids is measured by

Abstract: Under high-excitation irradiance conditions to induce fluorescence, the dependence of photobleaching of Coumarin 307 (C307) and acriflavine (ACF) laser dyes in liquid and solid phases have been studied. A cw LD laser source of 1 mW and 407 nm wavelength was used as an exciting source. For one hour exposure time, it was found that the solid dye samples suffer photobleaching more than the liquid dye samples. This is because in liquid solutions the dye molecules can circulate during the irradiation, while the photobleaching is a serious problem when the dye is incorporated into solid matrix and cannot circulate.

The Present research aimed at identifying:   

1- The level of environmental stress among preparatory students

2- The level of self-rebellion  among preparatory students

3- The correlation between the two variables of research (environmental stress and self-rebellion) and the extent to which the independent variable contributes to the variable of the middle school students. 

The current research has determined the students of the fifth stage of the preparatory stage and all the branches in the departments of education in Baghdad province the morning study for the academic

In this study, a different design of passive air Solar Chimney(SC)was tested by installing it in the south wall of insulated test room in Baghdad city. The SC was designed from vertical and inclined parts connected serially together, the vertical SC (first part) has a single pass and Thermal Energy Storage Box Collector (TESB (refined paraffin wax as Phase Change Material(PCM)-Copper Foam Matrix(CFM))), while the inclined SC was designed in single pass, double passes and double pass with TESB (semi refined paraffin wax with copper foam matrix) with selective working angle ((30^o, 45^o and 60^o). A computational model was employed and solved by Finite Volume Method (FVM) to simulate the air i

Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

Abstract Bilastine, a second-generation antihistamine, is commonly prescribed for managing allergic rhinoconjunctivitis and urticaria due to its prolonged action. However, its therapeutic potential is constrained by poor water solubility and low oral bioavailability. This study aimed to enhance bilastine dissolution and patient compliance by formulating a nanosuspension-based orodispersible film (ODF). An anti-solvent precipitation method was employed to produce nanosuspension using different hydrophilic stabilizers (Soluplus®, Poloxamer 188, and PEG 6000). The influence of formulation parameters, such as the stabilizer ratio, the anti-solvent ratio, stirring speed, and the stabilizer type, on particle size and polydispersity index (PDI)

This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number