It was aimed to investigate the compressibility, compactibility, powder flow and tablet disintegration of a new excipient comprising magnesium (Mg) silicate co-processed (5%–85% w/w) onto chitin, microcrystalline cellulose (MCC) and starch as the hydrophilic polymers of interest. Initially, the mechanism of tablet disintegration was studied by measuring water infiltration rate, moisture sorption, swelling capacity and hydration ability. Moreover, the powders compression behavior was carried out by applying Kawakita model of compression analysis in addition to porosity and radial tensile strength measurements. In vitro drug release of compacts made of 400 mg ibuprofen and 300 mg of the hydrophilic polymers containing 30% w/w Mg silicat

Due to the advantages over other metallic materials, such as superior corrosion resistance, excellent biocompatibility, and favorable mechanical properties, titanium, its alloys and related composites, are frequently utilized in biomedical applications, particularly in orthopedics and dentistry. This work focuses on developing novel titanium-titanium diboride (TiB2; ceramic material) composites for dental implants where TiB2 additions were estimated to be 9 wt.%. In a steel mold, Ti-TiB2 composites were fabricated using a powder metallurgy technique and sintered for five hours at 1200 °C. Microstructural and chemical properties were analyzed by energy dispersive X-ray spectroscopy (EDX), scanning electron microscopy (SEM), and X-ra

In recent years, observed focus greatly on gold nanoparticles synthesis due to its unique properties and tremendous applicability. In most of these researches, the citrate reduction method has been adopted. The aim of this study was to prepare and optimize monodisperse ultrafine particles by addition of reducing agent to gold salt, as a result of seed mediated growth mechanism. In this research, gold nanoparticles suspension (G) was prepared by traditional standard Turkevich method and optimized by studying different variables such as reactants concentrations, preparation temperature and stirring rate on controlling size and uniformity of nanoparticles through preparing twenty formulas (G1-G20). Subsequently, the selected formula that pr

An oral bi layer  sustained release (SR) strips of Sodium  Montelukast SMLT , which is selective  leukotriene  antagonist  , used  for  patients  suffered from mid-night asthma , were prepared successfully ,using different polymers, like guar  gum , carrageenan , and xanthan gum , by solvent casting method .

The results obtained by this study revealed  ,that best  fast  dissolving  film of  SMLT was  loaded  in carrageenan   polymer 57%  w\w (30mg.) ,  with  acceptable  physical properties, like film thickness , elastic endurance and  surface pH  .

Besides  to that , the  disintegration  t

 In the present work polymer electrolytes were formulated using the solvent casting technique. Under special conditions, the electrolyte content was of fixed ratio of polyvinylpyrolidone (PVP): polyacrylonitrile (PAN) (25:75), ethylene carbonate (EC) and propylene carbonate (PC) (1:1) with 10% of potassium iodide (KI) and iodine I₂ = 10% by weight of KI. The conductivity was increased with the addition of ZnO nanoparticles. It is also increased with the temperature increase within the range (293 to 343 K). The conductivity reaches maximum value of about (0.0296 S.cm^-1) with (0.25 g) ZnO. The results of FTIR for blend electrolytes indicated a significant degree of interaction between the polymer blend (PVP and PAN)

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a