Polymer films of PEG and PVA and their blend with different
concentrations of MnCl2 (0, 2, 4, 6 and 10 %.wt) were study using
casting technique. The X-ray spectra of pure PEG, PVA and
PVA:PEG films and with addition of 2% concentrations from
(MnCl2) show amorphous structures. The results for FTIR show the
interaction between the filler and polymer blend results in
decreasing crystallinity with rich amorphous phase. This
amorphous nature confirms the complexation between the filler and
the polymer blend. The optical properties of (PVA:PEG/MnCl2)
contain the recording of absorbance (A) and explain that the
absorption coefficient (α), refractive index (n), extinction coefficient
(ko) and the dielectric cons

Aim To develop a low-density polyethylene–hydroxyapatite (HA-PE) composite with properties tailored to function as a potential root canal filling material. Methodology Hydroxyapatite and polyethylene mixed with strontium oxide as a radiopacifier were extruded from a single screw extruder fitted with an appropriate die to form fibres. The composition of the composite was optimized with clinical handling and placement in the canal being the prime consideration. The fibres were characterized using infrared spectroscopy (FTIR), and their thermal properties determined using differential scanning calorimetry (DSC). The tensile strength and elastic modulus of the composite fibres and gutta-percha were compared, dry and after 1 month storage in

          The aim of the present study is to formulate, evaluate and characterize the nanoemulsion of Domperidone a poorly water-soluble anti-emetic drug.

           Domperidone powder is white or almost white powder, photosensitive, practically insoluble in water, slightly soluble in ethanol and in methanol; soluble in dimethylformamide. It is used as an antiemetic for the short-term treatment of nausea and vomiting of various etiologies.

           Solubility studies were conducted to select the oil, surfactant and cosurfactant. Phase diagrams were constructed by aqueous phase

This study was carried out to prepare and characterize domperidone nanoparticles to enhance solubility and the release rate. Domperidone is practically insoluble in water and has low and an erratic bioavailability range from 13%-17%. The domperidone nanoparticles were prepared by solvent/antisolvent precipitation method at different polymer:drug ratios of 1:1 and 2:1 using different polymers and grades of poly vinyl pyrolidone, hydroxy propyl methyl cellulose and sodium carboxymethyl cellulose as stabilizers. The effect of polymer type, ratio of polymer:drug, solvent:antisolvent ratio, stirring rate and stirring time on the particle size, were investigated and found to have a significant (p? 0.05) effect on particle size. The best formul

The problem motivation of this work deals with how to control the network overhead and reduce the network latency that may cause many unwanted loops resulting from using standard routing. This work proposes three different wireless routing protocols which they are originally using some advantages for famous wireless ad-hoc routing protocols such as dynamic source routing (DSR), optimized link state routing (OLSR), destination sequenced distance vector (DSDV) and zone routing protocol (ZRP). The first proposed routing protocol is presented an enhanced destination sequenced distance vector (E-DSDV) routing protocol, while the second proposed routing protocol is designed based on using the advantages of DSDV and ZRP and we named it as

Isradipine belong to dihydropyridine (DHP) class of calcium channel blockers (CCBs). It is  used in the treatment of hypertension, angina pectoris, in addition to Parkinson disease. It goes under the BCS class II drug (low solubility-high permeability). The drug will experience extensive first-pass metabolism in liver, therefore, oral bio-availability will be approximately15 to 24 %.

 The aim of this study was to formulate and optimize a stable  nanoparticles of a highly hydrophobic drug, isradipine by anti-solvent microprecipitation Method to achieve the higher in vitro dissolution rate, so that it will be absorbed by intestinal lymphatic transport in order to avoid hepatic first-pass metabolism&nbs

     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

In this work, chemical oxidation was used to polymerize conjugated polymer "Polypyrrole" at room temperature Graphene nanoparticles were added by in situ-polymerization to get (PPY-GN) nano. Optical and Electrical properties were studied for the nanocomposites. optical properties of the nanocomposites were studied by UV-Vis spectroscopy at wavelength range (200 -800 nm). The result showed optical absorption spectra were normally determined and the result showed that the maximum absorbance wave length at 280nm and 590nm. The optical energy gap has been evaluated by direct transition and the value has decreased from (2.1 eV for pure PPy) to (1.3 eV for 5 %wt. of GN). The optical constants such as the band tail width ΔE was evaluated, the