Arrested precipitation methode used to synthesize CuInSe2 (CIS) nanocrystals were added to a hot solvent with organic capping ligands to control nanocrystal formation and growth. CIS thin films deposited onto Soda-Lima Glass (SLG) substrate by spray-coat, then selenized in Ar-atmosphere to form CIS thin films. PVs were made with power conversion efficiencies of 0.631% as-deposited and 0.846% after selenization, for Mo coated, under AM 1.5 illuminations. (XRD) and (EDX) it is evident that CIS have chalcopyrite structure as the major phase with a preferred orientation along (112) direction and Cu:In:Se nanocrystals is nearly 1:1:2 atomic ratio.

The current trend worldwide is searching plant extracts towards prevention of neurodegenerative disorders. This study aimed to investigate the neuroprotective effect of Alpinia galanga leaves (ALE), Alpinia galanga rhizomes (ARE), Vitis vinifera seeds (VSE), Moringa oleifera leaves (MLE), Panax ginseng leaves (PLE) and Panax ginseng rhizomes (PRE) ethanolic extracts on human neuroblastoma (SHSY5Y) cells. The 1‐diphenyl‐1‐picrylhydrazyl (DPPH) radical scavenging of VSE and MLE were 81% and 58%, respectively. Ferric‐reducing antioxidant power (FRAP) of ALE and MLE (33.57 ± 0.20 and 26.76 ± 0.30 μmol Fe(ΙΙ)/g dry wt., respectively) were higher than for the other extracts. Liquid chromatography coupled to quadrupole time‐of‐fli

Ebastine (EBS) is a poorly water-soluble antihistaminic drug; it belongs to the class II group according to the biopharmaceutical classification system (BCS). The aim of the present work was to enhance the solubility, dissolution rate and micromeritic properties of the drug, by formulating it as spherical crystal agglomerates by Quasi Emulsion Solvent Diffusion (QESD) method.

Spherical crystal agglomerates (SCAs) were prepared in presence of three solvents dichloromethane (DCM), water and chloroform as a good solvent, poor solvent and bridging solvent respectively.  Agglomeration of EBS involved the use of some hydrophilic polymers like polyethylene glycol 4000 (PEG 4000), polyvinyl pyrrolidine K30 (PVP K30), D-?-tocopheryl

Separation of Trigonelline, the major alkaloid in fenugreek seeds, is difficult because the extract of these seeds usually contains Trigonelline, choline, mucilage, and steroidal saponins, in addition to some other substances. This study amis to isolate the quaternary ammonium alkaloid (Trigonelline) and choline from fenugreek seeds (Trigonella-foenum graecum L.) which have similar physiochemical properties by modifying of the classical method. Seeds were defatted and then extracted with methanol. The presence of alkaloids was detected by using Mayer's and Dragendorff's reagents. In this work, trigonilline was isolated with traces of choline by subsequent processes of purification using analytical and preparative TLC techniques.

The current study included the separation of three alkaloid compounds from Anastatica Hierochuntica and studied the effect of the these compounds on cancerous cells , specifically liver cancer it was found that compound number one is the most influential or inhibiting at 50 percent followed by compound number three when using concentration of 400 μg/mL.

Information from 54 Magnetic Resonance Imaging (MRI) brain tumor images (27 benign and 27 malignant) were collected and subjected to multilayer perceptron artificial neural network available on the well know software of IBM SPSS 17 (Statistical Package for the Social Sciences). After many attempts, automatic architecture was decided to be adopted in this research work. Thirteen shape and statistical characteristics of images were considered. The neural network revealed an 89.1 % of correct classification for the training sample and 100 % of correct classification for the test sample. The normalized importance of the considered characteristics showed that kurtosis accounted for 100 % which means that this variable has a substantial effect

The main aim of image compression is to reduce the its size to be able for transforming and storage, therefore many methods appeared to compress the image, one of these methods is "Multilayer Perceptron ". Multilayer Perceptron (MLP) method which is artificial neural network based on the Back-Propagation algorithm for compressing the image. In case this algorithm depends upon the number of neurons in the hidden layer only the above mentioned will not be quite enough to reach the desired results, then we have to take into consideration the standards which the compression process depend on to get the best results. We have trained a group of TIFF images with the size of (256*256)  in our research, compressed them by using MLP for each

Image Fusion Using A Convolutional Neural Network