Felodipine is a calcium-channel blocker with low aqueous solubility and bioavailability. Lipid dosage forms are attractive delivery systems for such hydrophobic drug molecules. Nanoemulsion (NE) is one of the popular methods that has been used to solve the dispersibility problems of many drugs. Felodipine was formulated as a NE utilizing oleic acid as an oil phase, tween 80 and tween 60 as surfactants and ethanol as a co-surfactant. Eight formulas were prepared, and different tests were performed to ensure the stability of the NEs, such as particle size, polydispersity index, zeta potential, dilution test, drug content, viscosity and in-vitro drug release. Results of characterization showed that felodipine nanoemulsion (F3) with (oleic acid 10%) ,(Smix 60% of tween80 :ethanol in a ratio of 3:1), (DDW 30%) was selected as the best formula, since it has a particle size of (17.01)nm, low PDI (0.392), zeta potential (-22.34mV), good dilution without drug precipitation , higher percent of drug content (99.098%) with acceptable viscosity , and complete release of the drug after (45 min.) with significantly higher (P<0.05) dissolution rate in comparison with the pure drug powder. The selected formula (F3) subjected to further investigations as drug and excipient compatibility study by Fourier transform infrared spectroscopy (FTIR) The outcomes of the (FTIR) explain that the distinctive peaks for felodipine were not affected by other components and displayed the same functional group's band with very slight shifting. This indicates that there was no interaction between felodipine and other NE components. Therefore, these excipients were found to be compatible with felodipine. In conclusion, the NE was found to be an efficient method to enhance the dispersibility and permeatioins of drugs that have poor water solubility (lipophilic drugs).
Machine learning is considered a powerful technique in many applications such as classification, clustering, recognition and prediction. Deep learning is a modern, vital and superior machine learning that gives stunning performance, especially with huge data. Stock market price prediction is the process of determining the future value of a prospect of a financial instrument traded in the market, to gain a great profit a successful prediction must be conducted, in order to achieve that machine learning is used, in this article, two approaches are proposed to predict the stock market prices and movement using two datasets, the first approach employs two machine learning models (J48 & logistic regression) while the second approach based on rec
... Show MoreThe last decade has seen a variety of modifications of glass-ionomer cements (GICs), such as inclusion of bioactive glass particles and dispensing systems. Hence, the aim was to systematically evaluate effect of mixing modes and presence of reactive glass additives on the physical properties of several GICs.
The physical properties of eight commercial restorative GICs; Fuji IX GP Extra (C&H), KetacTM Fill Plus Applicap (C&H), Fuji II LC (C&H), Glass Carbomer Ce
Rheumatoid arthritis is an autoimmune diseasecharacterized by chronic inflammationthat affects joints and cartilage. Bone complications such asRA-relatedosteoporosis are one of the most extra-articular manifestations. Many inflammatory mediators are released during RA disease pathophysiology; these mediators stimulate osteoclast genesis of bone by direct effects on RANKL and OPG. The study aimedto measure RANKL, OPG in RA patients treated with Etanercept only and other groups treated with Methotrexate onlyat baseline and after three months to evaluate bone state. An observational case-control prospective study was done on 30 RA patients who received MTX, 30 RA patients who received ETN, and 30 healthy,age-matched control groups. The
... Show MoreElectronic properties including (bond length, energy gap, HOMO, LUMO and density of state) as well as spectroscopic properties such like infrared, Raman scattering, force constant, reduced mass and longitu- dinal optical mode as a function of frequency are based on size and concentration of the molecular and nanostructures of aluminum nitride ALN, boron nitride BN and AlxB7-XN7 as nanotubes has calculated using Ab –initio approximation method dependent on density functional theory and generalized gradient approximation. The geometrical structure are calculated by using Gauss view 05 as a complementary program. Shows the energy gap of ALN, BN and AlxB7-XN7 as a function of the total number of atoms , start from smallest molecule to reached
... Show MoreTrace Elements (Cd, Pb, Cu, Zn, Ni) level were examined in hair of donors from industrial areas, cities and village, and in permanent contact with a polluted workplace environment in lattakia. Hair sample were analyzed for their contents of the trace elements by inductivity coupled plasma- mass spectrometer (ICP- MS). It was found that the contents of (Cd, Pb, Cu, Zn, Ni) in the hair were significantly higher in the industrial areas and cities, while in the village had the lower concentration of elements. Correlation coefficients between the levels of the elements in hair found in this study showed that hair is a good indicator of Environmental Pollution.
KE Sharquie, MM Al-Waiz, AA Al-Nuaimy, Saudi medical journal, 2005 - Cited by 8
In this paper a system is designed on an FPGA using a Nios II soft-core processor, to detect the colour of a specific surface and moving a robot arm accordingly. The surface being detected is bounded by a starting mark and an ending mark, to define the region of interest. The surface is also divided into sections as rows and columns and each section can have any colour. Such a system has so many uses like for example warehouses or even in stores where their storing areas can be divided to sections and each section is coloured and a robot arm collects objects from these sections according to the section’s colour also the robot arm can organize objects in sections according to the section’s colour.
The growing use of tele
This paper presents a new secret diffusion scheme called Round Key Permutation (RKP) based on the nonlinear, dynamic and pseudorandom permutation for encrypting images by block, since images are considered particular data because of their size and their information, which are two-dimensional nature and characterized by high redundancy and strong correlation. Firstly, the permutation table is calculated according to the master key and sub-keys. Secondly, scrambling pixels for each block to be encrypted will be done according the permutation table. Thereafter the AES encryption algorithm is used in the proposed cryptosystem by replacing the linear permutation of ShiftRows step with the nonlinear and secret pe
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