Artichoke (Cynara scolymus L.) is a nutritious vegetable that grown all over the world. It is a promising herbal plant, rich in bioactive components. It is considered as medicinal plant due to its nutritional and phytochemical composition, especially high proportion of phenolic compounds. The primary aim of this study was to achieve chemical profile analyses of artichoke for different phytochemcials, especially Scolymoside and Cynaroside. Methanolic crude was extracted from Artichoke leaves by rotary evaporator and separated by column chromatography. The fractions monitored by Thin Layer Chromatography (TLC), and identified in High-Pressure Liquid Chroma

             Polymeric microsphere devices occupy a wide range in the field of controlled drug delivery. Subcutaneous injectable preparations of Poly(Lactide-co-Glycolide) (PLGA) microsphere of Daptomycine were prepared by solvent extraction/evaporation technique using different copolymers ratio and molecular weights. Four formulations were prepared (F1-F4) and characterized in term of particle size, surface morphology, bulk density and porosity in addition to the drug content. The effects of the above parameters on the in-vitro release study were evaluated. These formulas were evaluated also for their in-vivo release profile using rat (as an animal model) and

The study included gross morphology and pollen of plants – which collected during field trips , and dry ones for most specimen preserved with the Iraqi herbaria – related to the genus Lycopus L. , and to identify the unidentified species and rectify the error there in , so according to that the species L. europaeus L. only were specified for the genus . Through this work the varity L. europaeus var. glabrescens Schmidely were found at the first time , and suggested to record anew for Iraq . Pollen were of medium size, and had an ellipsoid shape in the equatorial view , and hexagonal in the polar view. The ecological and soil quality where these genus plants grows were specified , and were geographically distribut

The cyanobacterial neurotoxinβ-N-methylamino-L-alanine (BMAA) is considered to be an “excitotoxin,” and its suggested mechanism of action is killing neurons. Long-term exposure to L-BMAA is believed to lead to neurodegenerative diseases including Parkinson’s and Alzheimer’s diseases and amyotrophic lateral sclerosis (Lou Gehrig’s disease). Objectives of this study were to determine the presumptive median lethal dose (LD₅₀), the Lowest-Observed-Adverse-Effect Level (LOAEL), and histopathologic lesions caused by the naturally occurring BMAA isomer, L-BMAA, in mice. Seventy NIH Swiss Outbred mice (35 male and 35 female) were used. Treatment group mice

Copper with different concentrations doped with zinc oxide nanoparticles were prepared from a mixture of zinc acetate and copper acetate with sodium hydroxide in aqueous solution. The structure of the prepared samples was done by X-ray diffraction, atomic force microscopy (AFM) and UV-VIS absorption spectrophotometer. Debye-Scherer formula was used to calculate the size of the prepared samples. The band gap of the nanoparticle ZnO was determined by using UV-VIS optical spectroscopy.

This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

KE Sharquie, AA Noaimi, MS Al-Zoubaidi, Journal of Cosmetics, Dermatological Sciences and Applications, 2015 - Cited by 8

Some maps of the chaotic firefly algorithm were selected to select variables for data on blood diseases and blood vessels obtained from Nasiriyah General Hospital where the data were tested and tracking the distribution of Gamma and it was concluded that a Chebyshevmap method is more efficient than a Sinusoidal map method through mean square error criterion.