Drug nanocrystals are nanoscopic crystals of the parent compound with dimensions less than 1 µm. A decrease in particle size will lead to an increase in effective surface area in the diffusion layer, which, in turn, increases the drug dissolution rate. Drug nanocrystals are one of the most important strategies to enhance the oral bioavailability of hydrophobic drugs.

Cefixime is the first member of what is generally termed the third generation orally active cephalosporins. These third generation cephalosporins are distinct from the older β-lactam antibiotics in their intensive antibacterial activity against a wide range of gram-negative bacteria.

The aim of this study is to prepare nanocrystals of cefixime as a caps

The current research aims to: 1- Identify the emotional sensitivity of children from the parents' point of view. 2- Identifying the differences in the emotional sensitivity of children from the parents ’point of view, according to the parents’ gender variable (father - mother). The basic research sample consisted of (285) male and female students from the sixth grade (primary school), chosen in a randomized stratified method from the districts (Al-Karkh and AlRasafa). While the sample of statistical analysis amounted to (200) father and (200) mothers of male and female students who were randomly selected from the sixth grade of the education directorates (Al-Karkh and Al-Rasafa). The two researchers also used a number of sta

The purpose of this study was to develop poloxamer-based in-situ gel of chloramphenicol aiming to increase bioavailability and prolong corneal contact time, controlling drug release, and enhancing ocular bioavailability. The in-situ gel was prepared using different concentrations of poloxamer 407 combined with hydroxypropyl methyl cellulose (HPMC) or carbapol 940 to achieve gelation temperature about physiological temperature and improve rheological behavior and gelling properties of poloxamer gel. The prepared formulations were evaluated for their appearance, pH, and sol-gel transition temperature. The formulations F₂, F₃, and F₅ have a gelation temperature within the accepted range 35-37⁰C an

1 - is not affected by illiteracy cells painful eggs after the first and seventh of the various concentrations used but found the effect of 21 and 35 days after treatment2 - repeat chromosomal aberrations illiteracy eggs cells no different distortions occurring sperm cells During Altnavra phase3 - increased chromosomal aberrations increase the dose especially for 21 and 35 days4 - The connective tissue is more sensitive phase of the pesticide from Altnavra phase

An experimental investigation has been carried out for zinc-nickel (Zn-Ni) electro-deposition using the constant applied current technique. Weight difference approach method was used to determine the cathode current efficiency and deposit thickness. Also, the influence effect of current density on the deposition process, solderability, and porosity of the plating layer in microelectronic applications were examined. The bath temperature effect on nickel composition and the form of the contract was studied using Scanning Electron Microscope (SEM). Moreover, elemental nature of the deposition was analyzed by Energy Dispersive X-Ray (EDX).     

It has been found that the best bath temperature

Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l