Liquisolid compact is the most promising technique for increasing dissolution rate and bioavailability of poorly soluble drugs.Clopidogrel bisulfate is an oral antiplatelets used for treatment and prophylaxis of cardiovacular and peripheral vascular diseases related to platelets aggreagation.Clopidogrel has low solubility at high pH media of intestine and low bioavailability of a bout 50% after oral doses.The purpose of this work was to enhance dissolution pattern of clopidogrel through its formulation into liquisolid tablets.A mathematical model was used to calculate the optimum quantities of tween 80 , carrier (Avicel PH 102) and coating material (Aerosil 200) needed to prepare acceptably flowing and compactible powder mixtures.The liq

Magnetic plaster kiln dust (MPKD) was synthesized as a unique, low-cost composite reused of byproduct plaster kiln dust (PKD), which is considered a source of air pollution. The FESEM, EDS, XRD, FTIR, VSM, and BET tests were used to characterize the MPKD. The characterization revealed that the MPKD was nanotubes non-agglomerated and super-paramagnetic with a high specific surface area (102.7 m²/g). Compared with the specific area of other materials (composites), the MPKD could be considered a promising substance in the field of water/wastewater treatment.

Clotrimazole (CLO) is an antimycotic imidazole derivative applied locally for the treatment of vaginal yeast infections. In this study, CLO was formulated as vaginal mucoadhesive hydrogel, using different types of mucoadhesive polymers to ensure prolonged contact between active ingredient and vaginal mucosa.

Physicochemical properties of the prepared formulas were evaluated as a visual inspection, pH, swelling index, spreadability, and mucoadhesive characteristics, in addition to an in-vitro drug release. The influence of type and concentration of polymers as CMC-Na (1.5, 2.5, and 3.5%w/w), carbopol 940( 0.25, 0.5, and 1 %w/w) and poloxamer 407 (15, 25, 30%w/w) on CLO release  from the prepared gels were also invest

Abstract 

Locally natural occurring Iraqi rocks of Bauxite and Porcelanite (after pre calcinations at 1000^oC for 1hr) were used, with the addition of different proportions of MgO and Al₂O₃, to prepare refractory materials. The effects of these additives on the physical and thermal properties of the prepared refractories were investigated.

Many batches of Bauxite/MgO, Bauxite/Al₂O₃, Bauxite/MgO/Al₂O₃, and   Porcelanite/ MgO/Al₂O₃ were prepared. The mixture is milled and classified into different size fractions; fine (less than 45μm) 40%, middle (45-75μm) 40%, and coarse (75-106μm) 20% .

The solar eclipse occurs at short time before the crescent birth moment when the moon near any one of moon orbit nodes It is important to determine the synchronic month which is used to find Higree date. The 'rules' of eclipses are: 

Y= ± 0.997  of Earth radius , the solar eclipse is central and 0.997 < |Y| < 1.026 the umbra cone touch the surface of the Earth, where Y is the least distance from the axis of the moon's shadow to the center of the Earth in units of the equatorial radius of the Earth.

A new model have been designed, depend on the horizontal coordinates of the sun, moon, the distances Earth-Moon (rm), Earth-sun (rs) and |Y| to determine the date and times of total solar eclipse and the geogra

Corrosion rate tests were carried out on carbon steel under concentration cells conditions of oxygen and sodium chloride. The effect of aeration in one compartment on the corrosion rate of both coupled metals was determined. In addition, the effects of time and temperatures on the corrosion rate of both coupled metals and galvanic currents between them were investigated. Corrosion potentials for the whole range of operating conditions under concentration cell conditions were also studied.   The results showed that under aeration condition, the formation of concentration cell caused a considerable corrosion rate of the Carbon steel specimens coupled in different concentrations of O₂ and NaCl due to the galvanic effect

Image 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

This work describes the development of new spectrophotometric techniques for 3-aminophenol assessment. The first technique involves using benzidine in an alkaline solution to convert 3-aminophenol into a colored complex. The produced complex has a red color with an absorbance of 462 nm. Between the concentration range 5–14 μg mL−1, Beer's law is obeyed with a correlation coefficient (R2) of 0.99781, a limit of detection (LOD) of 0.0423 μg mL−1, and a limit of quantification (LOQ) of 0.1411 μg mL−1. The recovery was between 87.2–95.43%, the relative standard deviation (%RSD) was 2.40–3.31% and the molar absorptivity was 3.545 × 103 L mol−1 cm−1. Secondly, cloud point extraction (CPE) was used to determ

Image 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